Risk prediction for severe pneumonia following congenital heart disease surgery in children

Objective To establish and validate a risk prediction model for severe pneumonia following cardiopulmonary bypass (CPB) in children with congenital heart disease. Methods All the children diagnosed with congenital heart disease and treated with CPB surgery in the Department of Thoracic Surgery, Chil...

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Main Authors: REN Chunnian, WU Chun, PAN Zhengxia, LI Yonggang
Format: Article
Language:zho
Published: Editorial Office of Journal of Third Military Medical University 2021-01-01
Series:Di-san junyi daxue xuebao
Subjects:
Online Access:https://aammt.tmmu.edu.cn/Upload/rhtml/202007232.htm
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spelling doaj-4411ef8bb4da4d90b5f76e962e78029e2021-04-14T00:30:21ZzhoEditorial Office of Journal of Third Military Medical UniversityDi-san junyi daxue xuebao1000-54042021-01-0143210911610.16016/j.1000-5404.202007232Risk prediction for severe pneumonia following congenital heart disease surgery in childrenREN Chunnian0 WU Chun1PAN Zhengxia2 LI Yonggang3Department of Cardiothoracic Surgery, Key Laboratory of Child Development and Disorders of Ministry of Education, Children's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Cardiothoracic Surgery, Key Laboratory of Child Development and Disorders of Ministry of Education, Children's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Cardiothoracic Surgery, Key Laboratory of Child Development and Disorders of Ministry of Education, Children's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Cardiothoracic Surgery, Key Laboratory of Child Development and Disorders of Ministry of Education, Children's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaObjective To establish and validate a risk prediction model for severe pneumonia following cardiopulmonary bypass (CPB) in children with congenital heart disease. Methods All the children diagnosed with congenital heart disease and treated with CPB surgery in the Department of Thoracic Surgery, Children's hospital of Chongqing Medical University from October 2014 to December 2017 were assigned into the modeling group (n=1 415), while those treated from December 2017 to October 2018 were enrolled into the validation group (n=393). The independent risk factors for severe pneumonia after surgery were screened using univariate and multivariate Logistic regression analysis, and the corresponding nomogram prediction model was constructed according to the regression coefficients. The receiver operating characteristic (ROC) curve and calibration curve were used respectively to evaluate the discriminant validity and calibration of the prediction model. Results The following 5 indicators were revealed to be the independent risk factors for severe pneumonia after CPB surgery: age, weight, preoperative hospital stay, score of Risk Adjustment in Congenital Heart Surgery-1 (RACHS-1) and time of cardiopulmonary bypass. Based on them, an individualized prediction model was established. The area under the curve (AUC) of the prediction model was 0.943 (95%CI: 0.929-0.954) and 0.925 (95%CI: 0.894-0.949) for the modeling and validation groups, indicating good discriminant validity. The P value of the calibration test was 0.592 and 0.256 for the 2 groups. Conclusion Our established individualized prediction model can be well used to evaluate the risk of severe pneumonia in children with congenital heart disease after CPB.https://aammt.tmmu.edu.cn/Upload/rhtml/202007232.htmcongenital heart diseasesurgerysevere pulmonary infectionrisk prediction modelchild
collection DOAJ
language zho
format Article
sources DOAJ
author REN Chunnian
WU Chun
PAN Zhengxia
LI Yonggang
spellingShingle REN Chunnian
WU Chun
PAN Zhengxia
LI Yonggang
Risk prediction for severe pneumonia following congenital heart disease surgery in children
Di-san junyi daxue xuebao
congenital heart disease
surgery
severe pulmonary infection
risk prediction model
child
author_facet REN Chunnian
WU Chun
PAN Zhengxia
LI Yonggang
author_sort REN Chunnian
title Risk prediction for severe pneumonia following congenital heart disease surgery in children
title_short Risk prediction for severe pneumonia following congenital heart disease surgery in children
title_full Risk prediction for severe pneumonia following congenital heart disease surgery in children
title_fullStr Risk prediction for severe pneumonia following congenital heart disease surgery in children
title_full_unstemmed Risk prediction for severe pneumonia following congenital heart disease surgery in children
title_sort risk prediction for severe pneumonia following congenital heart disease surgery in children
publisher Editorial Office of Journal of Third Military Medical University
series Di-san junyi daxue xuebao
issn 1000-5404
publishDate 2021-01-01
description Objective To establish and validate a risk prediction model for severe pneumonia following cardiopulmonary bypass (CPB) in children with congenital heart disease. Methods All the children diagnosed with congenital heart disease and treated with CPB surgery in the Department of Thoracic Surgery, Children's hospital of Chongqing Medical University from October 2014 to December 2017 were assigned into the modeling group (n=1 415), while those treated from December 2017 to October 2018 were enrolled into the validation group (n=393). The independent risk factors for severe pneumonia after surgery were screened using univariate and multivariate Logistic regression analysis, and the corresponding nomogram prediction model was constructed according to the regression coefficients. The receiver operating characteristic (ROC) curve and calibration curve were used respectively to evaluate the discriminant validity and calibration of the prediction model. Results The following 5 indicators were revealed to be the independent risk factors for severe pneumonia after CPB surgery: age, weight, preoperative hospital stay, score of Risk Adjustment in Congenital Heart Surgery-1 (RACHS-1) and time of cardiopulmonary bypass. Based on them, an individualized prediction model was established. The area under the curve (AUC) of the prediction model was 0.943 (95%CI: 0.929-0.954) and 0.925 (95%CI: 0.894-0.949) for the modeling and validation groups, indicating good discriminant validity. The P value of the calibration test was 0.592 and 0.256 for the 2 groups. Conclusion Our established individualized prediction model can be well used to evaluate the risk of severe pneumonia in children with congenital heart disease after CPB.
topic congenital heart disease
surgery
severe pulmonary infection
risk prediction model
child
url https://aammt.tmmu.edu.cn/Upload/rhtml/202007232.htm
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AT wuchun riskpredictionforseverepneumoniafollowingcongenitalheartdiseasesurgeryinchildren
AT panzhengxia riskpredictionforseverepneumoniafollowingcongenitalheartdiseasesurgeryinchildren
AT liyonggang riskpredictionforseverepneumoniafollowingcongenitalheartdiseasesurgeryinchildren
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